Method and device for implementing an FPGA-based large-scale radio frequency interference array correlator

Patent metadata

Field	Value
Publication number	US-11469838-B2
Application number	US-202017270871-A
Country	US
Kind code	B2
Filing date	May 25, 2020
Priority date	Feb 20, 2020
Publication date	Oct 11, 2022
Grant date	Oct 11, 2022

Abstract

A method and device for implementing an FPGA-based large-scale radio frequency interference array correlator are provided. The method includes: obtaining the number of channels of data of a radio frequency interference array, and performing average division; calculating the total correlation of data group and the total correlation between the data group and other data groups respectively through corresponding correlation calculation modules, and performing an accumulation calculation in an integration period to complete the total correlation operation of the radio frequency interference array. By means of grouping division and time division multiplexing, the FPGA resource is effectively utilized, and the calculation process of FPGA is simplified. The new method is suitable for the operation process of the system with high parallelism and high real-time requirements, and provides a high-efficiency solution for the real-time calculation of massive data of the large-scale radio frequency interference array.

First claim

What is claimed is:

1. A method for implementing an FPGA-based large-scale radio frequency interference array correlator, comprising:
step S 10 : according to a number M a of antennas of a radio frequency interference array and a polarization number M P of each antenna of the antennas, obtaining a number M of channels of data of the antennas of the radio frequency interference array;
step S 20 : averagely dividing M channels of data of the radio frequency interference array into N groups of data according to preset conditions, wherein each group of data of the N groups of data comprises K channels of data, and K=M/N; and
step S 30 : rearranging the N groups of data by a method of time division multiplexing, successively performing an auto-correlation calculation of the each group of data in the N groups of data through auto-correlation calculation modules and performing a cross-correlation calculation between the each group of data and other groups of data in the N groups of data through cross-correlation calculation modules, and completing a total correlation operation of the radio frequency interference array.

2. The method according to claim 1 , wherein the preset conditions are as follows:

Z
⁢

⁢
1
×

1

T
⁢
1

<

Z
⁢
2
×

1

T
⁢
2

;

Z
⁢

⁢
2

<
Z

;

wherein
,



⁢

Z
⁢

⁢
1

=

1
2

×
M
×

(

M
+
1

)

×
4
×

P
⁢
1

P

,

⁢

Z
⁢

⁢
2

=

[

1
2

×
K
×

(

K
+
1

)

×
B
⁢

⁢
1

+

K
×
K
×
B
⁢

⁢
2

]

×
4

,

P is a number of fast Fourier transform (FFT) points, P1 is a number of selected frequency points, T1 is a sampling clock, T2 is a processing clock of the FPGA-based large-scale radio frequency interference array correlator, B1 is a number of the auto-correlation calculation modules, B2 is a number of the cross-correlation calculation modules, and Z is a total number of multipliers in an FPGA chip.

3. The method according to claim 1 , wherein the auto-correlation calculation of a group of data in the N groups of data comprises an auto-correlation calculation and an accumulation calculation in an integration period of each channel of data in a data group, and a cross-correlation calculation and an accumulation calculation in the integration period between the each channel of data and other channels of data in the data group.

4. The method according to claim 1 , wherein the cross-correlation calculation between a group of data and another group of data in the N groups of data comprises a cross-correlation calculation and an accumulation calculation in an integration period between each channel of data in the group and each channel of data in another group.

5. The method according to claim 1 , wherein the method of time division multiplexing for rearranging the N groups of data in step S 30 comprises:
step S 31 : classifying the N groups of data into a first data sequence for the auto-correlation calculation, and a second data sequence for the cross-correlation calculation; and
step S 32 : averagely dividing the first data sequence and the second data sequence into segments according to a number of the auto-correlation calculation modules and a number of the cross-correlation calculation modules, respectively, performing the time division multiplexing on the auto-correlation correlation calculation modules and the cross-correlation calculation modules in each segment of the segments, and rearranging the N groups of data according to an operation of the each segment.

6. An FPGA-based large-scale radio frequency interference array correlator device, comprising a data receiving module, a writing control module, a cache module, a reading control module, a data rearrangement module, a correlation calculation module, and a packaging output module; wherein
the data receiving module is configured to obtain a first data packet and parse packet header information of the first data packet; wherein the first data packet contains antenna frequency domain data, and the packet header information comprises channel information and frequency point information;
the writing control module is configured to write the antenna frequency domain data to a cache posi

Assignees

• Inst Automation Cas
• Guangzhou Artificial Intelligence And Advanced Computing Inst Of Casia

Inventors

• Song Yafang
• Hao Jie
• Liang Jun
• Shu Lin
• Zhao Liangtian
• Fan Qiuxiang
• Feng Hui
• Hu Wenqing

Classifications

• G06F17/153 Primary

  Multidimensional correlation or convolution · CPC title

• H04B17/345 Primary

  Interference values ({signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]} H04B17/336) · CPC title

• H04B7/002

  Reducing depolarization effects · CPC title